Solar radiation estimations over India using Meteosat satellite images

India is endowed with good solar energy resource due to its geographic position in the equatorial Sun Belt of the earth, but its atmosphere can have eventual large presence of aerosols with the subsequent negative feedback to the solar radiation available. Therefore, solar resource assessment studies over India are of high interest for potential solar energy applications. In this work daily estimations of global horizontal and direct normal irradiation are presented for six locations in India covering the years from 2000 till 2007. These computations have been performed with IrSOLaV/CIEMAT method for computing solar radiation components from Meteosat images with a spatial resolution of less than 5 × 5 km. A brief assessment exercise of the model output have been made with ground measurements available from the World Radiation Data Centre database, which consists only of daily sums of global horizontal irradiation. The daily global horizontal irradiation estimated by the model has shown a general positive bias with the ground measurements in the range of 5%, being the root mean square deviation around 12%, excepting for Trivandrum location where there are evidences of higher uncertainty in the ground measurements. In addition, the dynamical behavior of daily global irradiation is quite well reproduced by the model as a consequence of adding to the input the daily turbidity values estimated from MODIS Terra satellite information. Estimations of direct normal irradiation are also exposed but no assessment was made due to the lack of ground measurements. The importance and need of accurate daily aerosol data with high spatial resolution for solar radiation estimations is pointed out in this work.     

Comprehending household cooking energy choice in rural India

Energy is essential to attain the quality of life and economic prosperity in a society. In the rural areas of India, cooking dominates the aggregate consumption of energy. This energy demand is mostly met by biomass fuels, which have many associated inherent disadvantages. Hence, it is important to understand the decision making process in rural households regarding the choice of cooking fuels. For this purpose, household information using the 61st round of National Sample Survey is analyzed for the rural parts of India. The logistic regression model is used to explain the determinants of clean fuel use for cooking purposes. The study shows that number of educated females between 10 and 50 years of age, average household education index, regular salary, and monthly per capita consumption expenditure have a positive and significant impact on probability of using clean cooking fuels, whereas possessing a Below Poverty Line ration card, belonging to reserved caste categories, family size and size of farm land have a significant negative linkage.     

Examining carbon emissions economic growth nexus for India: A multivariate cointegration approach

The study probes cointegration and causality between carbon emissions and economic growth for India using ARDL bounds testing approach complemented by Johansen–Juselius maximum likelihood procedure in a multivariate framework by incorporating energy supply, investment and employment for time span 1971–2006. The study fails to establish long-run equilibrium relationship and long term causality between carbon emissions and economic growth; however, there exists a bi-directional short-run causality between the two. Hence, in the short-run, any effort to reduce carbon emissions could lead to a fall in the national income. This study also establishes unidirectional short-run causality running from economic growth to energy supply and energy supply to carbon emissions. The absence of causality running from energy supply to economic growth implies that in India, energy conservation and energy efficiency measures can be implemented to minimize the wastage of energy across value chain. Such measures would narrow energy demand–supply gap. Absence of long-run causality between carbon emissions and economic growth implies that in the long-run, focus should be given on harnessing energy from clean sources to curb carbon emissions, which would not affect the country’s economic growth.     

Ecomasterplanning

Best known as the pioneer of the green skyscraper, Ken Yeang is now applying his innovative, ecological thinking to the urban masterplan. Here he outlines how the introduction of an ecoinfrastructure can bring multiple benefits to a city, encouraging connectivity between green spaces, providing natural habitats for wildlife and alleviating the impact of climate change by offsetting CO2 emissions. Copyright © 2008 John Wiley & Sons, Ltd.     

Do emerging markets matter in the world oil pricing system? Evidence of imported crude by China and India

This paper provides empirical evidence on the changing structure of world oil price system by identifying an additional driver-emerging market factor. We choose China and India as a representative of emerging markets to examine if the quantity of crude oil imported by China and India is significant in the existing oil pricing system (Kaufmann et al., 2004). Our data starts from January 2002 and ends in March 2010, which includes the oil shock of 2007–2008. We utilize cointegration and error correction model framework developed by Engle–Granger (1987) and Gregory–Hansen (1996) in the analysis. Our results indicate that demand from emerging markets has become a significant factor in the world oil pricing system since 2003. This result is significant as it lends empirical support to the widely held conjecture that the oil shock of 2007–2008 is a demand-led shock (Hamilton, 2009). Our result also has significant policy implications that go beyond the oil shock. The emerging market factor is there to stay and reflects the changing power between emerging and developed economies in the world economic system as a result of decades of fast economic development in the former. It will certainly influence policy issues related to oil and beyond.     

Decoupling urban transport from GHG emissions in Indian cities—A critical review and perspectives

How to sustain rapid economic and urban growth with minimised detriment to environment is a key challenge for sustainable development and climate change mitigation in developing countries, which face constraints of technical and financial resources scarcity as well as dearth of infrastructure governance capacity. This paper attempts to address this question by investigating the driving forces of transport demand and relevant policy measures that facilitate mitigating GHG emissions in the urban transport sector in Indian cities based on a critical review of the literature. Our overview of existing literature and international experiences suggests that it is critical to improve urban governance in transport infrastructure quality and develop efficient public transport, coupled with integrated land use/transport planning as well as economic instruments. This will allow Indian cities to embark on a sustainable growth pathway by decoupling transport services demand of GHG emissions in the longer term. Appropriate policy instruments need to be selected to reconcile the imperatives of economic and urban growth, aspiration to higher quality of life, improvements in social welfare, urban transport-related energy consumption and GHG emissions mitigation target in Indian cities.     

印度矿产资源现状与采矿研究

印度的金属矿产资源十分丰富,研究印度现在的矿产资源情况以及未来的资源需求的战略意义十分重大。文章重点研究了印度的煤矿开采历史和现状、煤炭资源的类型和储量分类以及矿业开采面临的一些问题和挑战。研究表明：印度共有资源种类89种,其中包括4种燃料矿物,11种金属矿物,52种非金属矿物和22种微量矿物。印度的煤炭总储量为2 460亿t,为世界第三大的煤炭生产国,印度煤炭的85%来自露天开采,15%来自井下开采。除煤炭以外,印度的重晶石、铬铁矿、滑石矿、铁矿石、锰矿、原钢、铝土矿、菱镁矿和钻石矿的储量均比较丰富。     

Improving access to biodiversity data for,and from,EIAs – a data publishing framework built to global standards

Biodiversity information obtained during environmental impact assessments (EIAs) is rarely accessible for other uses following the completion of the EIA. Such data need to be made readily accessible; adding them to publicly accessible national datasets is important if biodiversity science, conservation and future decisions based on environmental assessment are to benefit from new biodiversity data and improved biodiversity data coverage. An ‘EIA Biodiversity Data Publishing Framework’, based on the Global Biodiversity Information Facility (GBIF) global standards, is thus proposed to meet this need. This paper outlines the GBIF-catalysed initiative to establish such an operational framework for uptake by the EIA community, as well as options that are available for data publishing in the absence of such a framework. It reviews the current state of accessibility and management of the primary biodiversity data associated with EIA studies, and highlights the urgent need for uptake of a range of data-publishing tools and best practices for making EIA biodiversity data exchangeable using globally accepted standards. Lessons learnt from pilot projects in India and South Africa underline the call for the rapid uptake of a national-to-global scale EIA Biodiversity Data Publishing Framework.